Multi-Label Classifier Chains for Bird Sound

Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species. However, few works have considered the multi-label structure in birdsong. We propose to use an ensemble of classifier chains combined with a histogram-of-segments representation for multi-label classification of birdsong. The proposed method is compared with binary relevance and three multi-instance multi-label learning (MIML) algorithms from prior work (which focus more on structure in the sound, and less on structure in the label sets). Experiments are conducted on two real-world birdsong datasets, and show that the proposed method usually outperforms binary relevance (using the same features and base-classifier), and is better in some cases and worse in others compared to the MIML algorithms.Comment: 6 pages, 1 figure, submission to ICML 2013 workshop on bioacoustics. Note: this is a minor revision- the blind submission format has been replaced with one that shows author names, and a few corrections have been mad

Red deer exhibit spatial and temporal responses to hiking activity

Funding: This project is funded through a joint James Hutton Institute & University of St Andrews collaborative PhD Studentship, the Carnegie Trust and the British Deer Society.Outdoor recreation has the potential to impact the spatial and temporal distribution of animals. We explore interactions between red deer Cervus elaphus and hikers along a popular hiking path in the Scottish Highlands. We placed camera traps in transects at different distances (25, 75 and 150 m) from the path to study whether distance from hiker activity influences the number of deer detected. We compared this with the detection of red deer in an additional, spatially isolated area (one km away from any other transects and the hiking path). We collected count data on hikers at the start of the path and explored hourly (red deer detection during daytime), daily, diurnal (day versus night) and monthly spatial distributions of red deer. Using generalized linear mixed models with forward model selection, we found that the distribution of deer changed with the hiking activity. We found that fewer red deer were detected during busy hourly hiking periods. We found that during daytime, more red deer were detected at 150 m than at 25 m. Moreover, during the day, red deer were detected at a greater rate in the isolated area than around the transects close to the path and more likely to be found close to the path at night. This suggests that avoidance of hikers by red deer, in this study area, takes place over distances greater than 75 m and that red deer are displaced into less disturbed areas when the hiking path is busy. Our results suggest that the impact of hikers is short-term, as deer return to the disturbed areas during the night.Publisher PDFPeer reviewe

Red deer behavioural response to hiking activity : a study using camera traps

With increasing levels of outdoor recreation activities, consequences for wildlife through interactions with recreationists are highly variable. Behavioural changes in wildlife are one potential consequence of interactions with outdoor recreationists. In ungulate populations, vigilance and flight responses are well-known antipredator behaviours, and an increase in their level indicates a more intense stress level which, ultimately, can have consequences for animal fitness. In Scotland, the geographical distribution of red deer (Cervus elaphus) overlaps greatly with areas used for popular outdoor activities such as hill walking. In this piece of research, we studied red deer time allocation, vigilance, and flight behaviours near a popular hiking path using camera traps. We positioned the cameras in transects at different distances (25, 75, and 150 m) from the path and recorded hiking activity using an automated people counter. Red deer behaviour was categorized from photo analysis as (1) no response (e.g. feeding and resting), (2) vigilant (i.e. upright head position), and (3) flight response. We also investigated demographic variables (group size and sex) and the direction of red deer movement relative to the trail. We used generalised linear mixed models to analyse behaviour in relation to the distance from the hiking track, hiking activity, time of the day, demographic, and environmental variables. We did not find an increase in vigilance or flight behaviour in relation to the distance from the hiking path or the hiking activity. These results suggest that red deer, in our study area, are habituated to the presence of hikers and may spatially avoid areas close to the hiking path instead of displaying cost-intensive behaviour (i.e. flight or vigilance behaviour).Publisher PDFPeer reviewe

Spatial and temporal variations in interspecific interaction : impact of a recreational landscape

Anthropogenic activities, such as outdoor recreation, have the potential to change complex interactions between wildlife and livestock, with further consequences for the management of both animals, the environment, and disease transmission. We present the interaction amongst wildlife, livestock, and outdoor recreationists as a three-way interaction. Little is known about how recreational activities alter the interaction between herbivores in areas extensively used for recreational purposes. We investigate how hiking activity affects spatio-temporal co-occurrence between domestic sheep (Ovis aries) and red deer (Cervus elaphus). We used camera traps to capture the spatio-temporal distribution of red deer and sheep and used the distance from the hiking path as a proxy of hiking activity. We used generalized linear models to investigate the spatial distribution of sheep and deer. We analysed the activity patterns of sheep and deer and then calculated their coefficients of temporal overlap for each camera trap location. We compared these coefficients in relation to the distance from the hiking path. Finally, we used a generalized linear mixed-model to investigate which factors influence the spatio-temporal succession between deer and sheep. We do not find that sheep and red deer spatially avoid each other. The coefficient of temporal overlap varied with distance from the hiking trail, with stronger temporal co-occurrence at greater distances from the hiking trail. Red deer were more likely to be detected further from the path during the day, which increased the temporal overlap with sheep in these areas. This suggests that hiking pressure influences spatio-temporal interactions between sheep and deer, leading to greater temporal overlap in areas further from the hiking path due to red deer spatial avoidance of hikers. This impact of recreationists on the wildlife and livestock interaction can have consequences for the animals’ welfare, the vegetation they graze, their management, and disease transmission.Publisher PDFPeer reviewe

Reconstructing Velocities of Migrating Birds from Weather Radar – A Case Study in Computational Sustainability

Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the US there is an operational network of weather radars providing freely accessible data for monitoring meteorological phenomena in the atmosphere. Individual radars are sensitive enough to detect birds, and can provide insight into migratory behaviors of birds at scales that are not possible using other sensors. Archived data from the WSR-88D network of US weather radars hold valuable and detailed information about the continent-scale migratory movements of birds over the last 20 years. However, significant technical challenges must be overcome to understand this information and harness its potential for science and conservation. We describe recent work on an AI system to quantify bird migration using radar data, which is part of the larger BirdCast project to model and forecast bird migration at large scales using radar, weather, and citizen science data

Explaining Reinforcement Learning to Mere Mortals: An Empirical Study

We present a user study to investigate the impact of explanations on non-experts' understanding of reinforcement learning (RL) agents. We investigate both a common RL visualization, saliency maps (the focus of attention), and a more recent explanation type, reward-decomposition bars (predictions of future types of rewards). We designed a 124 participant, four-treatment experiment to compare participants' mental models of an RL agent in a simple Real-Time Strategy (RTS) game. Our results show that the combination of both saliency and reward bars were needed to achieve a statistically significant improvement in mental model score over the control. In addition, our qualitative analysis of the data reveals a number of effects for further study.Comment: 7 page

Reconstructing Velocities of Migrating Birds from Weather Radar – A Case Study in Computational Sustainability

Bird migration occurs at the largest of global scales, but monitoring such movements can be challenging. In the US there is an operational network of weather radars providing freely accessible data for monitoring meteorological phenomena in the atmosphere. Individual radars are sensitive enough to detect birds, and can provide insight into migratory behaviors of birds at scales that are not possible using other sensors. Archived data from the WSR-88D network of US weather radars hold valuable and detailed information about the continent-scale migratory movements of birds over the last 20 years. However, significant technical challenges must be overcome to understand this information and harness its potential for science and conservation. We describe recent work on an AI system to quantify bird migration using radar data, which is part of the larger BirdCast project to model and forecast bird migration at large scales using radar, weather, and citizen science data

A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA

Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne “contamination,” and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration patterns presented here will be essential for biological and conservation applications. These descriptions help to define migration phenology in time and space, fill knowledge gaps in avian annual cycles, and are useful for monitoring long-term population trends of migrants. Furthermore, these descriptions will aid in assessing potential risks to migrants, particularly from structures with which birds collide and artificial lighting that disorients migrants.This is the publisher’s final pdf. The published article is copyrighted by the Ecological Society of America and can be found at: http://esajournals.onlinelibrary.wiley.com/hub/journal/10.1002/%28ISSN%291939-5582/Keywords: spatio-temporal patterns, BirdCast, quantitative description, nocturnal migration, WSR-88D, radar ornitholog

Sugarcane (Saccharum X officinarum): A Reference Study for the Regulation of Genetically Modified Cultivars in Brazil

Global interest in sugarcane has increased significantly in recent years due to its economic impact on sustainable energy production. Sugarcane breeding and better agronomic practices have contributed to a huge increase in sugarcane yield in the last 30 years. Additional increases in sugarcane yield are expected to result from the use of biotechnology tools in the near future. Genetically modified (GM) sugarcane that incorporates genes to increase resistance to biotic and abiotic stresses could play a major role in achieving this goal. However, to bring GM sugarcane to the market, it is necessary to follow a regulatory process that will evaluate the environmental and health impacts of this crop. The regulatory review process is usually accomplished through a comparison of the biology and composition of the GM cultivar and a non-GM counterpart. This review intends to provide information on non-GM sugarcane biology, genetics, breeding, agronomic management, processing, products and byproducts, as well as the current technologies used to develop GM sugarcane, with the aim of assisting regulators in the decision-making process regarding the commercial release of GM sugarcane cultivars

Predicting Task-Specific Webpages for Revisiting

With the increased use of the web has come a corresponding increase in information overload that users face when trying to locate specific webpages, especially as a majority of visits to webpages are revisits. While automatically created browsing history lists offer a potential low-cost solution to re-locating webpages, even short browsing sessions generate a glut of webpages that do not relate to the user's information need or have no revisit value. We address how we can better support web users who want to return to information on a webpage that they have previously visited by building more useful history lists. The paper reports on a combination technique that semi-automatically segments the webpage browsing history list into tasks, applies heuristics to remove webpages that carry no intrinsic revisit value, and uses a learning model, sensitive to individual users and tasks, that predicts which webpages are likely to be revisited again. We present results from an empirical evaluation that report the likely revisit need of users and that show that adequate overall prediction accuracy can be achieved. This approach can be used to increase utility of history lists by removing information overload to users when revisiting webpages